Various tests have been used to characterize the mechanical properties of material samples, particularly of polymer plastics and elastomer or rubbery materials. In one short-term category are impact tests such as Izod impact, and Durometer testing. A thin piece of material is placed on a hard surface and impacted by a hard object at varying kinetic energies until permanent deformation or rupture is observed. Other hardness tests array materials according to which material will scratch which softer material, for example, diamond scratching sapphire, sapphire scratching quartz, etc. Creep properties are less often determined, since the testing is time-consuming. Samples may be subjected to a constant stress for an extended period at a controlled temperature while strain is measured, resulting in a graph of a time-dependent modulus of elasticity, the xe2x80x9ccreep modulus,xe2x80x9d representing the ratio of stress to strain plotted as a function of time. Since strain increases over time at constant stress due to material creep, the creep modulus is a decreasing function of time. Families of creep modulus graphs are typically plotted for selected fixed stresses and fixed temperatures. Creep modulus graphs commonly extend from a first measurement at one hour (of sustained stress) to 1000 hours or more. Each graph in a family of creep modulus graphs requires that a separate material sample be maintained at a separate temperature and stress in a test apparatus for the full duration, for example, 1000 hours, indicating the time-consuming and expensive nature of the testing. For testing of dynamic stress/strain relationships on an intermediate time scale between very short-term impact and very long-term creep, machines are sometimes employed that impose programmable progressively-increasing or cyclically-changing strain over time while measuring stress, typically over a time scale of seconds to minutes. Instron is a widely recognized manufacturer of devices for this kind of testing. Controlled strain is commonly applied to soft materials, especially elastomers, while stress is measured. On harder materials, where it can be difficult to control strain, stress is varied while strain is measured. In a common testing protocol, stress is increased monotonically while strain is measured. When a specified strain threshold is reached, typically where the material deviates from more or less reversible elastic behavior to plastic strain and permanent deformation, this threshold defines the yield stress. Complete failure or rupture of the sample defines ultimate stress, sometimes called tensile stress. In metals, material samples may be subjected to cyclic stress over millions of cycles at various stress levels, defining a fatigue stress threshold below which samples cease to exhibit progressive weakening or embrittlement leading to failure.
The traditional tests described above, usually not involving programmable test equipment, suffer from several limitations. The longer term tests involving sustained stresses at controlled temperature tie up equipment for long periods of time. Where process control is involved, the value of test data declines rapidly with the time it takes to obtain the data. While impact and scratch hardness types of tests provide quick results, tests for creep properties are far too slow to provide information for tuning real-time process parameters that produce the material. The short term tests measure only a failure threshold under a fixed set of conditions, providing little insight into other material properties. Combining test results can reveal material properties over wide-ranging conditions, but the results do not generate a predictive analytic model that could describe material response to a set of conditions outside the specific conditions of the test results. It would be desirable that test results could be used to define a predictive model of material properties, applicable to describing dynamic response of individual cells in a Finite Element Analysis, or FEA. Families of measured curves obtained under dynamic conditions and at varying temperatures provide a wealth of data that have not been reducible to a predictive model, even when the data span the conditions of concern for actual use of the material.
In U.S. Pat. No. 6,332,364 (2001), Buschmann et. al. describe a universal testing device capable of applying a programmable actuator for controlling a displacement imposed on a sample, a load cell for measuring the force associated with that displacement, data collection and signal conditioning apparatus, and control over humidity. Being programmable, this or a similar device can be made to test the stress response of a sample to an arbitrary time-varying strain. By appropriate feedback control to obtain a desired time-varying strain, such a device can be made to test the strain response for programmed time-varying stress. An earlier, simpler system is described by Sambrook et. al. in U.S. Pat. No. 4,074,569 (1978), where the device provides for preloading a sample, then causing the load to change abruptly to a fixed test load exceeding the preload, and then measuring a visco-elastic strain response to the test load over time. While Sambrook et. al. contemplate measurement of a time-dependent stress/strain relationship, and while Buschmann et. al. provide programmable actuation and sensing means that could potentially explore a complex, non-linear and time-dependent stress/strain dynamic, they provide no means for extracting meaningful simplifications or descriptive parameters from the multitude of testing possibilities. Sambrook et. al. further describe means for temperature control of the sample, recognizing that temperature is an important part of such a dynamic description, particularly in visco-elastic materials. Buschmann et. al. similarly recognize humidity as an important parameter.
The difficulty with conventional methods is the proliferation of possibilities for data collection over differing stresses, strains, temperatures, humidities, and the time-sequences involving these variables, without a method for reducing the data to a concise set of useful parameters. Such a method might appear to be provided by the teaching of Koopmann et. al. in U.S. Pat. No. 4,238,952 (1980), whose objective (from the Summary of the Invention) is xe2x80x9cdetermining characteristic rheological quantities of viscoelastic materials, in particular rubber and rubber mixtures . . . . xe2x80x9d Indeed, test data are boiled down to just two parameters, a viscosity and an elasticity, which are incorporated into a formula to describe stress/strain behavior. The method, however, is applicable only to a small class of rubbery substances, those soft enough to sustain an abrupt 60% compressive deformation without damage. One would desire some means for comparing viscoelastic properties over a wide range of materials spanning, for example, from latex rubber to hard neoprene rubber, and on to polypropylene, and on to polycarbonate. Lacking in the prior art is any integrated method of testing, data simplification, and predictive modeling of stress/strain behavior, applicable to a wide variety of materials under widely varying conditions of stress, time, and temperature.
As with nonlinear stress and strain in solids, a limited understanding of the dynamic properties of magnetic materials has limited the testing and characterization of these materials. Curve fitting techniques are used to capture initial magnetization curves of virgin samples, while coercive force and saturation values are used to approximate the character of a hysteresis loop at very high cyclic excitation, but the descriptors do not predict, for example, how small hysteresis loops behave for small cyclic excitations, with or without magnetic bias. In both solid mechanics and magnetics, very detailed models suffer from becoming too specialized, being applicable only to very particular materials under very particular conditions.
Better modeling, striking a compromise between true and accurate description on the one hand, and generality of application on the other hand, has the potential to lead to better testing, better quality control in manufacture and receiving, and better insight into how the materials behave and might be improved.
In light of the above-described limitations in material testing and characterization, it is one object to provide a dynamic software model by which the establishment of a small number of material parameters causes the model to predict strain when stress is varied dynamically or stress when strain is varied dynamically. A related object is that the software model predict how material response is affected by temperature. Another related object is that the software model take statistical account of the dynamics of multiple internal states of sub-microscopic components of a material whose properties are not uniform on a molecular scale. A further related object is that the statistical accounting include a model of energy transition domains, each one capable of occupying two or more semi-stable energy states at differing microscopic strain dislocations, with state transitions being promoted by thermal agitation and either promoted or inhibited by stress communicated from the surrounding material.
It is an object to provide an information processing system that calculates and adjusts material parameters of a dynamic stress/strain software model to obtain a best-fit match to data measured for a material sample, whereby these best-fit parameters characterize the sample and permit prediction of material stress/strain responses under variable simulated conditions, including conditions beyond or not produced in the testing phase. It is an object to provide means for bringing dynamic materials data to an information processing system as just described, so that a material can be characterized. In one embodiment, it is an object to provide means for importing pre-existing material test data into the information processing system for characterization to obviate at least some measurement trials.
In another embodiment, it is an object to provide mechanical testing means that imposes varying influences such as stresses and temperature conditions upon one or more material samples over time, those conditions probing the range of properties associated with the model parameters, such that the information processing system can reliably and accurately resolve those parameters from the test data. It is a related object to simplify the mechanical testing means, and to minimize the number of samples of a given material required for a characterization, and to abbreviate the time period required for characterization, in order to optimize the overall economy and utility of the mechanical testing means and associated information system, consistent with the overall system yielding accurate characterizations of materials over a usefully broad range of dynamic conditions.
It is a further related object that the testing means measure stress/strain responses for both increasing and decreasing or reversing stress, that both the increases and decreases include rapid increases and rapid decreases, that the measured responses further include response to stresses sustained for long periods and responses for sustained recovery periods after stress reduction or removal or reversal, and that these varied response measurements include responses from widely differing temperatures.
In a related context rooted in the same phenomena of thermal physics and the same fundamental statistical analysis approach, it is an object to characterize ferromagnetic and ferrimagnetic materials, both permanent and xe2x80x9csoftxe2x80x9d materials, through an improved model, through a method for matching model parameters to empirical data, and through devices and methods for improved testing, to probe deeply into the response space of the material.